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Record W4405061868 · doi:10.31861/geo.2024.847.155-168

Territorial and temporal features of the land structure of the physical and geographical districts of the Chernivtsi region

2024· article· en· W4405061868 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientific Herald of Chernivtsi University Geography · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicScientific Research and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyLand useAgricultural landWork (physics)Economic geographyRegional scienceAgricultureEnvironmental resource managementEcologyEnvironmental scienceArchaeology

Abstract

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The characterization of the dynamics of certain categories of land in respective landscapes, either with or without considering the latter, has been the focus of domestic and foreign scholars. It should be noted that the former has become intensively interested in this issue relatively recently, since the twenty-first century. In particular, over the past 10 years, O. Butrym has assessed the structure of the land fund with the determination of the peculiarities of its use based on the analysis of the level of anthropogenic load and environmental stability of the territory of the Kyiv oblast, and substantiated the directions of improving the ecological balance of land use in the region. The current state and peculiarities of the use of the land fund of the Vinnytsia region, its component structure, and peculiarities of its territorial differentiation are examined in the collective work of O. Sukhyi, K. Darchuk, N. Zelena. The results of the current state and use of land resources in the Khmelnytskyi oblast, where the largest areas are occupied by agricultural land, are presented by V. Lapchynskyi and O. Boiko. The basic principles of optimizing the landscapes of Central Podillia based on the study of the structure and dynamics with a scheme of rational organization of their territory were proposed by L. Kostiv in her dissertation study. Abroad, the issue of temporal dynamics of the main categories of land in the physiographic region has been prominent since the second half of the twentieth century. A study of a series of 19 maps by land use categories was developed by R. Dolan, B. Hayden, and C. Vincent in the 1970s. They provided recommendations for a remote sensing system for monitoring the coastal zone in the context of the dynamics of their studied landscapes. Monica Goigel Turner developed spatial simulation models based on historical aerial photography to predict temporal changes in land use patterns in the foothill district of Georgia (USA) in five land use categories: urban, agricultural, deserted, pasture, and forest. Changes in land use and landscape structure in the agricultural landscape in the central Czech Republic were studied by Z. Lipský. He paid special attention to the major changes that occurred during the 40 years of socialist collectivism. The site of intensive tripartite land use between urban, agricultural, and natural use and its derived problems near Niagara Falls (Ontario) for the period 1935–1981 was studied by Michael R. Muller and John Middleton. We assessed the temporal dynamics of the main categories of land in the territory of 24 physical-geographical regions, which are part of 6 physical-geographical sections: Prut-Dniester upland forest-steppe region, Prut-Siret upland forest-meadow region, Skyba mid-mountain forest Carpathians, Verkhovyna lowland forest-meadow Carpathians, Polonynian-Chornohora subalpine forest Carpathians, and Marmarosh mid-mountain subalpine forested Carpathians. The characterization of each of the 24 aforementioned physical-geographical regions aims to consider changes in anthropogenic pressure on each component of the land fund by type of use and management during the 2004–2016 period. Our goal is also to identify trends that may lead, given the specified method of use, to changes in certain ecosystems or loss of the landscape's original appearance. The temporal dynamics of the main categories of land were considered in the territory of 24 physical-geographical regions, which are part of 6 agricultural sections. The Prut-Dniester upland region, situated as a watershed between the Dniester and Prut river systems and characterized by a flat forest-steppe landscape type, is the most developed agricultural region and exhibits a clearly defined agricultural specialization. In general, the analysis indicates a tendency of clear dominance of two types of land in the land structure of each of the physical-geographical regions – agricultural and forested. The Prut-Dniester Upland Forest-Steppe Region stands out within the generalized group of agricultural and forest lands. Among the 8 districts of this region, 3 (Dolyniany-Balkivtsi, Zastavna, and Oselivka) have a very high share of agricultural land: 87 %, 85 %, and 83 %, respectively. The next subgroup with large values of agricultural land includes 3 more districts of the Prut-Dniester region: Kelmentsi, Novoselytsia, and Kitsman, where agricultural land is utilized on 75–79 % of their territory. The third subgroup in Prut-Dniester is formed by Khotyn and Sokyriany physical-geographical regions with an almost balanced structure of agricultural and forest land. Starting from the Skyba mid-mountain forested Carpathians and upwards, the ratio of agricultural and forest land varies in places. In 5 physical-geographical regions of the Carpathians (Berehomet, Shurdyn, Maksymets, Yarovytsia, Chornodil), the share of forests is very high – more than 75.1 %. The share of agricultural land in all these physical-geographical regions is less than 33.2 %. The exceptions are Putyla and Cheremosh, where the share of agricultural land is the highest (34 %) among all the highland regions. Thus, 11 regions have the largest relative shares (> 75.1 %) of agricultural (6 regions) and forest (5 regions) land. The combined total structural analysis of the lands in Chernivtsi Oblast's physical-geographical regions revealed the presence of a formed Dniester-Prut-Siret macro-centre, a Sokyriany mini-centre with a positive land structure, and the Polonyna-Chornohora-Marmaros physical-geographical region centre with a negative land ratio. The Dniester-Prut-Siret mega-centre encompasses approximately 50.9 % of the area of Chernivtsi Oblast, within which the Brusnytsia physical-geographical region, with a satisfactory land structure, is located as an island element. The Sokyriany mini-centre, exhibiting a good-to-best combination of land, is situated in the extreme east of Chernivtsi Oblast and covers 15.2 % of its area. The Polonyna-Chornohora-Marmaros physical-geographical region centre, characterized by poor and worst land structure, accounts for 33.9 % of the territorial area. Keywords: physiographic region, land structure, rating analysis, rating evaluation.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.200
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it